Finding pixel-wise matches between two input images and thus the corresponding disparities leads to a disparity image.
Hereby, the correctness of the result greatly depends on the matching function and the optimization strategies that are used.
The optimization strategies are typically categorized into local and global approaches.
While local methods rely on a fixed neighbourhood around a central pixel, global methods optimize an energy function on the full image domain.
Due to the finite window size, local methods are very efficient but often lack in accuracy [1]}.
